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12 Nov 2025 Job Information Organisation/Company University of Innsbruck Department Faculty of Law Research Field Juridical sciences Researcher Profile First Stage Researcher (R1) Country Austria
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. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine learning models without moving sensitive or large
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6 Nov 2025 Job Information Organisation/Company Luleå tekniska universitet Research Field Computer science Researcher Profile First Stage Researcher (R1) Country Sweden Application Deadline 27 Nov
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values rest on credibility, trust and security. By having the courage to think freely and innovate, our actions together, large and small, contribute to a better world. We look forward to receiving your
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
technological breakthroughs or large-scale adoption events. The module will be validated on both historical datasets and scenario data generated by Integrated Assessment Models (IAMs), large climate-economic
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12 Nov 2025 Job Information Organisation/Company University of Innsbruck Department Faculty of Engineering Sciences Research Field Technology » Energy technology Researcher Profile First Stage
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. (2017). Beyond prediction: Using big data for policy problems. Science, 355(6324), 483–485. Barocas, S., Hardt, M., & Narayanan, A. (2021). Fairness in Machine Learning. Retrieved from https
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simulation workload and update the solver data structures when the mesh changes. These approaches would be applied on modern large-scale heterogeneous parallel computing environments where both CPUs and GPUs
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will use a high-fidelity large eddy simulation (LES) code and scientific machine learning tools, such as real-time optimisers, in order to simulate wind farms exposed to various atmospheric inflows. Some
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and arms for both autonomous and prosthetic applications. If you’re excited by all this, we encourage you to apply. The opening: In this project, you will develop: Detailed, large-scale computer models